library(tidyverse)## ── Attaching packages ────────────────────────────────── tidyverse 1.2.1 ──## ✔ ggplot2 3.2.0 ✔ purrr 0.3.2
## ✔ tibble 2.1.3 ✔ dplyr 0.8.3
## ✔ tidyr 0.8.3 ✔ stringr 1.4.0
## ✔ readr 1.3.1 ✔ forcats 0.3.0## ── Conflicts ───────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(gganimate)
library(gapminder)
library(plotly)##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutdata("gapminder")
glimpse(gapminder)## Observations: 1,704
## Variables: 6
## $ country <fct> Afghanistan, Afghanistan, Afghanistan, Afghanistan, Af…
## $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, …
## $ lifeExp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854…
## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 148803…
## $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.…hist(gapminder$year)
hist(gapminder$lifeExp)
hist(gapminder$pop,breaks=100)
hist(gapminder$gdpPercap,breaks = 50)
table(gapminder$country,gapminder$continent)##
## Africa Americas Asia Europe Oceania
## Afghanistan 0 0 12 0 0
## Albania 0 0 0 12 0
## Algeria 12 0 0 0 0
## Angola 12 0 0 0 0
## Argentina 0 12 0 0 0
## Australia 0 0 0 0 12
## Austria 0 0 0 12 0
## Bahrain 0 0 12 0 0
## Bangladesh 0 0 12 0 0
## Belgium 0 0 0 12 0
## Benin 12 0 0 0 0
## Bolivia 0 12 0 0 0
## Bosnia and Herzegovina 0 0 0 12 0
## Botswana 12 0 0 0 0
## Brazil 0 12 0 0 0
## Bulgaria 0 0 0 12 0
## Burkina Faso 12 0 0 0 0
## Burundi 12 0 0 0 0
## Cambodia 0 0 12 0 0
## Cameroon 12 0 0 0 0
## Canada 0 12 0 0 0
## Central African Republic 12 0 0 0 0
## Chad 12 0 0 0 0
## Chile 0 12 0 0 0
## China 0 0 12 0 0
## Colombia 0 12 0 0 0
## Comoros 12 0 0 0 0
## Congo, Dem. Rep. 12 0 0 0 0
## Congo, Rep. 12 0 0 0 0
## Costa Rica 0 12 0 0 0
## Cote d'Ivoire 12 0 0 0 0
## Croatia 0 0 0 12 0
## Cuba 0 12 0 0 0
## Czech Republic 0 0 0 12 0
## Denmark 0 0 0 12 0
## Djibouti 12 0 0 0 0
## Dominican Republic 0 12 0 0 0
## Ecuador 0 12 0 0 0
## Egypt 12 0 0 0 0
## El Salvador 0 12 0 0 0
## Equatorial Guinea 12 0 0 0 0
## Eritrea 12 0 0 0 0
## Ethiopia 12 0 0 0 0
## Finland 0 0 0 12 0
## France 0 0 0 12 0
## Gabon 12 0 0 0 0
## Gambia 12 0 0 0 0
## Germany 0 0 0 12 0
## Ghana 12 0 0 0 0
## Greece 0 0 0 12 0
## Guatemala 0 12 0 0 0
## Guinea 12 0 0 0 0
## Guinea-Bissau 12 0 0 0 0
## Haiti 0 12 0 0 0
## Honduras 0 12 0 0 0
## Hong Kong, China 0 0 12 0 0
## Hungary 0 0 0 12 0
## Iceland 0 0 0 12 0
## India 0 0 12 0 0
## Indonesia 0 0 12 0 0
## Iran 0 0 12 0 0
## Iraq 0 0 12 0 0
## Ireland 0 0 0 12 0
## Israel 0 0 12 0 0
## Italy 0 0 0 12 0
## Jamaica 0 12 0 0 0
## Japan 0 0 12 0 0
## Jordan 0 0 12 0 0
## Kenya 12 0 0 0 0
## Korea, Dem. Rep. 0 0 12 0 0
## Korea, Rep. 0 0 12 0 0
## Kuwait 0 0 12 0 0
## Lebanon 0 0 12 0 0
## Lesotho 12 0 0 0 0
## Liberia 12 0 0 0 0
## Libya 12 0 0 0 0
## Madagascar 12 0 0 0 0
## Malawi 12 0 0 0 0
## Malaysia 0 0 12 0 0
## Mali 12 0 0 0 0
## Mauritania 12 0 0 0 0
## Mauritius 12 0 0 0 0
## Mexico 0 12 0 0 0
## Mongolia 0 0 12 0 0
## Montenegro 0 0 0 12 0
## Morocco 12 0 0 0 0
## Mozambique 12 0 0 0 0
## Myanmar 0 0 12 0 0
## Namibia 12 0 0 0 0
## Nepal 0 0 12 0 0
## Netherlands 0 0 0 12 0
## New Zealand 0 0 0 0 12
## Nicaragua 0 12 0 0 0
## Niger 12 0 0 0 0
## Nigeria 12 0 0 0 0
## Norway 0 0 0 12 0
## Oman 0 0 12 0 0
## Pakistan 0 0 12 0 0
## Panama 0 12 0 0 0
## Paraguay 0 12 0 0 0
## Peru 0 12 0 0 0
## Philippines 0 0 12 0 0
## Poland 0 0 0 12 0
## Portugal 0 0 0 12 0
## Puerto Rico 0 12 0 0 0
## Reunion 12 0 0 0 0
## Romania 0 0 0 12 0
## Rwanda 12 0 0 0 0
## Sao Tome and Principe 12 0 0 0 0
## Saudi Arabia 0 0 12 0 0
## Senegal 12 0 0 0 0
## Serbia 0 0 0 12 0
## Sierra Leone 12 0 0 0 0
## Singapore 0 0 12 0 0
## Slovak Republic 0 0 0 12 0
## Slovenia 0 0 0 12 0
## Somalia 12 0 0 0 0
## South Africa 12 0 0 0 0
## Spain 0 0 0 12 0
## Sri Lanka 0 0 12 0 0
## Sudan 12 0 0 0 0
## Swaziland 12 0 0 0 0
## Sweden 0 0 0 12 0
## Switzerland 0 0 0 12 0
## Syria 0 0 12 0 0
## Taiwan 0 0 12 0 0
## Tanzania 12 0 0 0 0
## Thailand 0 0 12 0 0
## Togo 12 0 0 0 0
## Trinidad and Tobago 0 12 0 0 0
## Tunisia 12 0 0 0 0
## Turkey 0 0 0 12 0
## Uganda 12 0 0 0 0
## United Kingdom 0 0 0 12 0
## United States 0 12 0 0 0
## Uruguay 0 12 0 0 0
## Venezuela 0 12 0 0 0
## Vietnam 0 0 12 0 0
## West Bank and Gaza 0 0 12 0 0
## Yemen, Rep. 0 0 12 0 0
## Zambia 12 0 0 0 0
## Zimbabwe 12 0 0 0 0xtabs(~ gapminder$continent + gapminder$country)## gapminder$country
## gapminder$continent Afghanistan Albania Algeria Angola Argentina Australia
## Africa 0 0 12 12 0 0
## Americas 0 0 0 0 12 0
## Asia 12 0 0 0 0 0
## Europe 0 12 0 0 0 0
## Oceania 0 0 0 0 0 12
## gapminder$country
## gapminder$continent Austria Bahrain Bangladesh Belgium Benin Bolivia
## Africa 0 0 0 0 12 0
## Americas 0 0 0 0 0 12
## Asia 0 12 12 0 0 0
## Europe 12 0 0 12 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Bosnia and Herzegovina Botswana Brazil Bulgaria
## Africa 0 12 0 0
## Americas 0 0 12 0
## Asia 0 0 0 0
## Europe 12 0 0 12
## Oceania 0 0 0 0
## gapminder$country
## gapminder$continent Burkina Faso Burundi Cambodia Cameroon Canada
## Africa 12 12 0 12 0
## Americas 0 0 0 0 12
## Asia 0 0 12 0 0
## Europe 0 0 0 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Central African Republic Chad Chile China Colombia
## Africa 12 12 0 0 0
## Americas 0 0 12 0 12
## Asia 0 0 0 12 0
## Europe 0 0 0 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Comoros Congo, Dem. Rep. Congo, Rep. Costa Rica
## Africa 12 12 12 0
## Americas 0 0 0 12
## Asia 0 0 0 0
## Europe 0 0 0 0
## Oceania 0 0 0 0
## gapminder$country
## gapminder$continent Cote d'Ivoire Croatia Cuba Czech Republic Denmark
## Africa 12 0 0 0 0
## Americas 0 0 12 0 0
## Asia 0 0 0 0 0
## Europe 0 12 0 12 12
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Djibouti Dominican Republic Ecuador Egypt El Salvador
## Africa 12 0 0 12 0
## Americas 0 12 12 0 12
## Asia 0 0 0 0 0
## Europe 0 0 0 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Equatorial Guinea Eritrea Ethiopia Finland France
## Africa 12 12 12 0 0
## Americas 0 0 0 0 0
## Asia 0 0 0 0 0
## Europe 0 0 0 12 12
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Gabon Gambia Germany Ghana Greece Guatemala Guinea
## Africa 12 12 0 12 0 0 12
## Americas 0 0 0 0 0 12 0
## Asia 0 0 0 0 0 0 0
## Europe 0 0 12 0 12 0 0
## Oceania 0 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Guinea-Bissau Haiti Honduras Hong Kong, China Hungary
## Africa 12 0 0 0 0
## Americas 0 12 12 0 0
## Asia 0 0 0 12 0
## Europe 0 0 0 0 12
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Iceland India Indonesia Iran Iraq Ireland Israel Italy
## Africa 0 0 0 0 0 0 0 0
## Americas 0 0 0 0 0 0 0 0
## Asia 0 12 12 12 12 0 12 0
## Europe 12 0 0 0 0 12 0 12
## Oceania 0 0 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Jamaica Japan Jordan Kenya Korea, Dem. Rep.
## Africa 0 0 0 12 0
## Americas 12 0 0 0 0
## Asia 0 12 12 0 12
## Europe 0 0 0 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Korea, Rep. Kuwait Lebanon Lesotho Liberia Libya
## Africa 0 0 0 12 12 12
## Americas 0 0 0 0 0 0
## Asia 12 12 12 0 0 0
## Europe 0 0 0 0 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Madagascar Malawi Malaysia Mali Mauritania Mauritius
## Africa 12 12 0 12 12 12
## Americas 0 0 0 0 0 0
## Asia 0 0 12 0 0 0
## Europe 0 0 0 0 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Mexico Mongolia Montenegro Morocco Mozambique Myanmar
## Africa 0 0 0 12 12 0
## Americas 12 0 0 0 0 0
## Asia 0 12 0 0 0 12
## Europe 0 0 12 0 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Namibia Nepal Netherlands New Zealand Nicaragua Niger
## Africa 12 0 0 0 0 12
## Americas 0 0 0 0 12 0
## Asia 0 12 0 0 0 0
## Europe 0 0 12 0 0 0
## Oceania 0 0 0 12 0 0
## gapminder$country
## gapminder$continent Nigeria Norway Oman Pakistan Panama Paraguay Peru
## Africa 12 0 0 0 0 0 0
## Americas 0 0 0 0 12 12 12
## Asia 0 0 12 12 0 0 0
## Europe 0 12 0 0 0 0 0
## Oceania 0 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Philippines Poland Portugal Puerto Rico Reunion
## Africa 0 0 0 0 12
## Americas 0 0 0 12 0
## Asia 12 0 0 0 0
## Europe 0 12 12 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Romania Rwanda Sao Tome and Principe Saudi Arabia
## Africa 0 12 12 0
## Americas 0 0 0 0
## Asia 0 0 0 12
## Europe 12 0 0 0
## Oceania 0 0 0 0
## gapminder$country
## gapminder$continent Senegal Serbia Sierra Leone Singapore Slovak Republic
## Africa 12 0 12 0 0
## Americas 0 0 0 0 0
## Asia 0 0 0 12 0
## Europe 0 12 0 0 12
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Slovenia Somalia South Africa Spain Sri Lanka Sudan
## Africa 0 12 12 0 0 12
## Americas 0 0 0 0 0 0
## Asia 0 0 0 0 12 0
## Europe 12 0 0 12 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Swaziland Sweden Switzerland Syria Taiwan Tanzania
## Africa 12 0 0 0 0 12
## Americas 0 0 0 0 0 0
## Asia 0 0 0 12 12 0
## Europe 0 12 12 0 0 0
## Oceania 0 0 0 0 0 0
## gapminder$country
## gapminder$continent Thailand Togo Trinidad and Tobago Tunisia Turkey
## Africa 0 12 0 12 0
## Americas 0 0 12 0 0
## Asia 12 0 0 0 0
## Europe 0 0 0 0 12
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Uganda United Kingdom United States Uruguay Venezuela
## Africa 12 0 0 0 0
## Americas 0 0 12 12 12
## Asia 0 0 0 0 0
## Europe 0 12 0 0 0
## Oceania 0 0 0 0 0
## gapminder$country
## gapminder$continent Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe
## Africa 0 0 0 12 12
## Americas 0 0 0 0 0
## Asia 12 12 12 0 0
## Europe 0 0 0 0 0
## Oceania 0 0 0 0 0uniqcountries <- function(x){gapminder %>%
filter(continent == x) %>%
select(country) %>% unique()
}
names(gapminder)## [1] "country" "continent" "year" "lifeExp" "pop" "gdpPercap"ggplot(gapminder,aes(x=country,y=lifeExp)) +
geom_boxplot() + facet_wrap(~continent)
ggplot(gapminder,aes(x=year,y=lifeExp)) +
geom_point() + facet_wrap(~continent) +
geom_smooth(se=FALSE,aes(color=country),show.legend = FALSE)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
# africa by itself
fig1 <- gapminder %>% filter(continent == "Africa") %>%
ggplot(aes(x=year,y=lifeExp)) +
geom_point() +
geom_smooth(se=FALSE,aes(color=country),show.legend = TRUE)
# neato!
ggplotly(fig1)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'# oceania
fig2 <- gapminder %>% filter(continent == "Oceania") %>%
ggplot(aes(x=year,y=lifeExp)) +
geom_point() +
geom_smooth(se=FALSE,aes(color=country),show.legend = TRUE)
fig2 + lims(y=c(0,100))## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
ggplotly(fig2)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'p1 = ggplot(gapminder, aes(x=year,y=lifeExp,color=continent)) +
geom_smooth(se=FALSE)
p2 = ggplot(gapminder, aes(x=gdpPercap,y=lifeExp,color=continent,size=pop)) +
geom_point()
gridExtra::grid.arrange(p1,p2)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
ggplot(gapminder, aes(y=gdpPercap,x=year,color=continent)) +
geom_smooth(se=FALSE)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
p2 + facet_wrap(~year) + scale_x_log10()
ggplot(gapminder,aes(x=year,y=pop,color=continent)) +
geom_point() + geom_smooth(se=FALSE)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
p3 = gapminder %>% filter(continent=="Asia") %>%
ggplot(aes(x=year,y=pop,color=country)) +
geom_point() + geom_smooth(se=FALSE)
# neato zoom!
ggplotly(p3)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'ggplot(gapminder, aes(x=gdpPercap, y=lifeExp, size = pop, colour = country)) +
geom_point(alpha = 0.7, show.legend = FALSE) +
scale_colour_manual(values = country_colors) +
scale_size(range = c(2, 12)) +
scale_x_log10() +
facet_wrap(~continent) + labs(subtitle = "Points scaled to country population") +
# Here comes the gganimate specific bits
labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
transition_time(year) +
ease_aes('linear')